{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "z: 0.05019548907876015\n",
      "\n",
      "idx: 366, landmark: x: 0.7556626200675964\n",
      "y: 0.3966195583343506\n",
      "z: 0.08838354796171188\n",
      "\n",
      "idx: 367, landmark: x: 0.7358204126358032\n",
      "y: 0.490213543176651\n",
      "z: 0.04781778156757355\n",
      "\n",
      "idx: 368, landmark: x: 0.737900972366333\n",
      "y: 0.30328819155693054\n",
      "z: 0.08487318456172943\n",
      "\n",
      "idx: 369, landmark: x: 0.6641128659248352\n",
      "y: 0.5611751079559326\n",
      "z: -0.019099770113825798\n",
      "\n",
      "idx: 370, landmark: x: 0.5991846919059753\n",
      "y: 0.4060768187046051\n",
      "z: -0.0532471165060997\n",
      "\n",
      "idx: 371, landmark: x: 0.6472987532615662\n",
      "y: 0.3756518065929413\n",
      "z: -0.012302783317863941\n",
      "\n",
      "idx: 372, landmark: x: 0.7328262329101562\n",
      "y: 0.3248730003833771\n",
      "z: 0.06002655252814293\n",
      "\n",
      "idx: 373, landmark: x: 0.673486053943634\n",
      "y: 0.3157235383987427\n",
      "z: 0.0181833878159523\n",
      "\n",
      "idx: 374, landmark: x: 0.6627830862998962\n",
      "y: 0.3164214789867401\n",
      "z: 0.015157753601670265\n",
      "\n",
      "idx: 375, landmark: x: 0.6524492502212524\n",
      "y: 0.4816659092903137\n",
      "z: -0.018001966178417206\n",
      "\n",
      "idx: 376, landmark: x: 0.7401659488677979\n",
      "y: 0.41754230856895447\n",
      "z: 0.040117111057043076\n",
      "\n",
      "idx: 377, landmark: x: 0.6395830512046814\n",
      "y: 0.5861666798591614\n",
      "z: -0.018218034878373146\n",
      "\n",
      "idx: 378, landmark: x: 0.6839903593063354\n",
      "y: 0.5657587647438049\n",
      "z: 0.011371796950697899\n",
      "\n",
      "idx: 379, landmark: x: 0.7022045254707336\n",
      "y: 0.552293598651886\n",
      "z: 0.028638144955039024\n",
      "\n",
      "idx: 380, landmark: x: 0.6521959900856018\n",
      "y: 0.3158310353755951\n",
      "z: 0.015155342407524586\n",
      "\n",
      "idx: 381, landmark: x: 0.6421620845794678\n",
      "y: 0.31442418694496155\n",
      "z: 0.01760529726743698\n",
      "\n",
      "idx: 382, landmark: x: 0.6350706219673157\n",
      "y: 0.31366515159606934\n",
      "z: 0.02102377638220787\n",
      "\n",
      "idx: 383, landmark: x: 0.7277711033821106\n",
      "y: 0.3003421425819397\n",
      "z: 0.050899211317300797\n",
      "\n",
      "idx: 384, landmark: x: 0.6428766846656799\n",
      "y: 0.3037036657333374\n",
      "z: 0.017568038776516914\n",
      "\n",
      "idx: 385, landmark: x: 0.6542506814002991\n",
      "y: 0.3002433776855469\n",
      "z: 0.01466390397399664\n",
      "\n",
      "idx: 386, landmark: x: 0.6656579971313477\n",
      "y: 0.2997528910636902\n",
      "z: 0.014774671755731106\n",
      "\n",
      "idx: 387, landmark: x: 0.6767053008079529\n",
      "y: 0.3017968535423279\n",
      "z: 0.017227347940206528\n",
      "\n",
      "idx: 388, landmark: x: 0.6834014058113098\n",
      "y: 0.3048539459705353\n",
      "z: 0.02109551429748535\n",
      "\n",
      "idx: 389, landmark: x: 0.7477457523345947\n",
      "y: 0.3015378415584564\n",
      "z: 0.1241530254483223\n",
      "\n",
      "idx: 390, landmark: x: 0.6806466579437256\n",
      "y: 0.3142055571079254\n",
      "z: 0.022257434204220772\n",
      "\n",
      "idx: 391, landmark: x: 0.6434237360954285\n",
      "y: 0.4321076571941376\n",
      "z: -0.0319620817899704\n",
      "\n",
      "idx: 392, landmark: x: 0.6281125545501709\n",
      "y: 0.39671820402145386\n",
      "z: -0.04222624748945236\n",
      "\n",
      "idx: 393, landmark: x: 0.615472137928009\n",
      "y: 0.42607077956199646\n",
      "z: -0.043757326900959015\n",
      "\n",
      "idx: 394, landmark: x: 0.7023641467094421\n",
      "y: 0.5303485989570618\n",
      "z: 0.013815249316394329\n",
      "\n",
      "idx: 395, landmark: x: 0.6843297481536865\n",
      "y: 0.5461376905441284\n",
      "z: -0.0020945495925843716\n",
      "\n",
      "idx: 396, landmark: x: 0.6378126740455627\n",
      "y: 0.5721211433410645\n",
      "z: -0.033400993794202805\n",
      "\n",
      "idx: 397, landmark: x: 0.737011194229126\n",
      "y: 0.5121679306030273\n",
      "z: 0.07746139168739319\n",
      "\n",
      "idx: 398, landmark: x: 0.6348342299461365\n",
      "y: 0.30888670682907104\n",
      "z: 0.020090928301215172\n",
      "\n",
      "idx: 399, landmark: x: 0.6131346225738525\n",
      "y: 0.3421386778354645\n",
      "z: -0.02942998893558979\n",
      "\n",
      "idx: 400, landmark: x: 0.6638223528862\n",
      "y: 0.57735276222229\n",
      "z: -0.006522223819047213\n",
      "\n",
      "idx: 401, landmark: x: 0.7544263601303101\n",
      "y: 0.4310001730918884\n",
      "z: 0.08066651225090027\n",
      "\n",
      "idx: 402, landmark: x: 0.6250098943710327\n",
      "y: 0.4813868999481201\n",
      "z: -0.03005422092974186\n",
      "\n",
      "idx: 403, landmark: x: 0.6287909150123596\n",
      "y: 0.48583248257637024\n",
      "z: -0.0333196185529232\n",
      "\n",
      "idx: 404, landmark: x: 0.6325153112411499\n",
      "y: 0.492296040058136\n",
      "z: -0.0368841290473938\n",
      "\n",
      "idx: 405, landmark: x: 0.6356059908866882\n",
      "y: 0.4999969005584717\n",
      "z: -0.03631467744708061\n",
      "\n",
      "idx: 406, landmark: x: 0.6418399810791016\n",
      "y: 0.5115550756454468\n",
      "z: -0.029326442629098892\n",
      "\n",
      "idx: 407, landmark: x: 0.6449350118637085\n",
      "y: 0.4700198769569397\n",
      "z: -0.019872168079018593\n",
      "\n",
      "idx: 408, landmark: x: 0.6488807201385498\n",
      "y: 0.46847984194755554\n",
      "z: -0.019848838448524475\n",
      "\n",
      "idx: 409, landmark: x: 0.6523054838180542\n",
      "y: 0.4665675759315491\n",
      "z: -0.01973148249089718\n",
      "\n",
      "idx: 410, landmark: x: 0.6694291830062866\n",
      "y: 0.455924391746521\n",
      "z: -0.01629381626844406\n",
      "\n",
      "idx: 411, landmark: x: 0.7203593850135803\n",
      "y: 0.4220234751701355\n",
      "z: 0.01273293886333704\n",
      "\n",
      "idx: 412, landmark: x: 0.6124841570854187\n",
      "y: 0.32982784509658813\n",
      "z: -0.014772516675293446\n",
      "\n",
      "idx: 413, landmark: x: 0.6201215386390686\n",
      "y: 0.30087220668792725\n",
      "z: 0.014233763329684734\n",
      "\n",
      "idx: 414, landmark: x: 0.6289421319961548\n",
      "y: 0.3030809462070465\n",
      "z: 0.01870902068912983\n",
      "\n",
      "idx: 415, landmark: x: 0.6414533853530884\n",
      "y: 0.470778226852417\n",
      "z: -0.018829556182026863\n",
      "\n",
      "idx: 416, landmark: x: 0.7262074947357178\n",
      "y: 0.4632006883621216\n",
      "z: 0.027181537821888924\n",
      "\n",
      "idx: 417, landmark: x: 0.6068161725997925\n",
      "y: 0.2997022271156311\n",
      "z: -0.003740281332284212\n",
      "\n",
      "idx: 418, landmark: x: 0.6503955125808716\n",
      "y: 0.52690589427948\n",
      "z: -0.02547074481844902\n",
      "\n",
      "idx: 419, landmark: x: 0.6026715636253357\n",
      "y: 0.3336232900619507\n",
      "z: -0.037070050835609436\n",
      "\n",
      "idx: 420, landmark: x: 0.6247429847717285\n",
      "y: 0.3647516965866089\n",
      "z: -0.03322187066078186\n",
      "\n",
      "idx: 421, landmark: x: 0.6276020407676697\n",
      "y: 0.5360372066497803\n",
      "z: -0.03482399135828018\n",
      "\n",
      "idx: 422, landmark: x: 0.6812804341316223\n",
      "y: 0.4962799847126007\n",
      "z: -0.007535651326179504\n",
      "\n",
      "idx: 423, landmark: x: 0.6564581394195557\n",
      "y: 0.4070000648498535\n",
      "z: -0.014813737943768501\n",
      "\n",
      "idx: 424, landmark: x: 0.6677722930908203\n",
      "y: 0.5139237642288208\n",
      "z: -0.01624240353703499\n",
      "\n",
      "idx: 425, landmark: x: 0.6872203946113586\n",
      "y: 0.40524059534072876\n",
      "z: -0.009982232004404068\n",
      "\n",
      "idx: 426, landmark: x: 0.6699550151824951\n",
      "y: 0.42301076650619507\n",
      "z: -0.014796451665461063\n",
      "\n",
      "idx: 427, landmark: x: 0.7014917731285095\n",
      "y: 0.43196046352386475\n",
      "z: -0.0025677871890366077\n",
      "\n",
      "idx: 428, landmark: x: 0.633726954460144\n",
      "y: 0.5548495054244995\n",
      "z: -0.03729313239455223\n",
      "\n",
      "idx: 429, landmark: x: 0.6348873376846313\n",
      "y: 0.3740317225456238\n",
      "z: -0.02521790750324726\n",
      "\n",
      "idx: 430, landmark: x: 0.6951082348823547\n",
      "y: 0.5097469091415405\n",
      "z: 0.0021772694308310747\n",
      "\n",
      "idx: 431, landmark: x: 0.6775034666061401\n",
      "y: 0.5278491973876953\n",
      "z: -0.009292417205870152\n",
      "\n",
      "idx: 432, landmark: x: 0.690608024597168\n",
      "y: 0.47516700625419617\n",
      "z: -0.003739010076969862\n",
      "\n",
      "idx: 433, landmark: x: 0.738924503326416\n",
      "y: 0.44537606835365295\n",
      "z: 0.04092570021748543\n",
      "\n",
      "idx: 434, landmark: x: 0.7093299031257629\n",
      "y: 0.4790534973144531\n",
      "z: 0.008555904030799866\n",
      "\n",
      "idx: 435, landmark: x: 0.7491145133972168\n",
      "y: 0.4626137614250183\n",
      "z: 0.06928790360689163\n",
      "\n",
      "idx: 436, landmark: x: 0.6826520562171936\n",
      "y: 0.444425106048584\n",
      "z: -0.01086411438882351\n",
      "\n",
      "idx: 437, landmark: x: 0.6231107711791992\n",
      "y: 0.3530554473400116\n",
      "z: -0.021694447845220566\n",
      "\n",
      "idx: 438, landmark: x: 0.6243709325790405\n",
      "y: 0.390138179063797\n",
      "z: -0.05826988071203232\n",
      "\n",
      "idx: 439, landmark: x: 0.6344178318977356\n",
      "y: 0.39564192295074463\n",
      "z: -0.04465273395180702\n",
      "\n",
      "idx: 440, landmark: x: 0.6172104477882385\n",
      "y: 0.3791961371898651\n",
      "z: -0.06707888096570969\n",
      "\n",
      "idx: 441, landmark: x: 0.6312217712402344\n",
      "y: 0.28669121861457825\n",
      "z: 0.011434237472712994\n",
      "\n",
      "idx: 442, landmark: x: 0.6536896824836731\n",
      "y: 0.2778152823448181\n",
      "z: 0.008391511626541615\n",
      "\n",
      "idx: 443, landmark: x: 0.6733636260032654\n",
      "y: 0.27705812454223633\n",
      "z: 0.007633225526660681\n",
      "\n",
      "idx: 444, landmark: x: 0.6894351840019226\n",
      "y: 0.281273752450943\n",
      "z: 0.011944008059799671\n",
      "\n",
      "idx: 445, landmark: x: 0.7003290057182312\n",
      "y: 0.2891883850097656\n",
      "z: 0.019700538367033005\n",
      "\n",
      "idx: 446, landmark: x: 0.7069206833839417\n",
      "y: 0.3155929446220398\n",
      "z: 0.03746838495135307\n",
      "\n",
      "idx: 447, landmark: x: 0.7541202306747437\n",
      "y: 0.36429452896118164\n",
      "z: 0.09116356074810028\n",
      "\n",
      "idx: 448, landmark: x: 0.6958420872688293\n",
      "y: 0.3345411419868469\n",
      "z: 0.024233950302004814\n",
      "\n",
      "idx: 449, landmark: x: 0.6817072629928589\n",
      "y: 0.33771812915802\n",
      "z: 0.01601998135447502\n",
      "\n",
      "idx: 450, landmark: x: 0.6636059284210205\n",
      "y: 0.3365707993507385\n",
      "z: 0.010937538929283619\n",
      "\n",
      "idx: 451, landmark: x: 0.646830677986145\n",
      "y: 0.3328942656517029\n",
      "z: 0.010037829168140888\n",
      "\n",
      "idx: 452, landmark: x: 0.6339556574821472\n",
      "y: 0.3283751606941223\n",
      "z: 0.01056336797773838\n",
      "\n",
      "idx: 453, landmark: x: 0.6248076558113098\n",
      "y: 0.32371294498443604\n",
      "z: 0.010746294632554054\n",
      "\n",
      "idx: 454, landmark: x: 0.7571091055870056\n",
      "y: 0.3728411793708801\n",
      "z: 0.14390015602111816\n",
      "\n",
      "idx: 455, landmark: x: 0.6347770094871521\n",
      "y: 0.4007328450679779\n",
      "z: -0.038318946957588196\n",
      "\n",
      "idx: 456, landmark: x: 0.6135313510894775\n",
      "y: 0.35362136363983154\n",
      "z: -0.042770616710186005\n",
      "\n",
      "idx: 457, landmark: x: 0.6139295101165771\n",
      "y: 0.38999485969543457\n",
      "z: -0.06899098306894302\n",
      "\n",
      "idx: 458, landmark: x: 0.6068881154060364\n",
      "y: 0.39921486377716064\n",
      "z: -0.06453167647123337\n",
      "\n",
      "idx: 459, landmark: x: 0.614169716835022\n",
      "y: 0.3936871290206909\n",
      "z: -0.0625782459974289\n",
      "\n",
      "idx: 460, landmark: x: 0.6312922239303589\n",
      "y: 0.4061436951160431\n",
      "z: -0.034288786351680756\n",
      "\n",
      "idx: 461, landmark: x: 0.6043035387992859\n",
      "y: 0.4001975357532501\n",
      "z: -0.06834764778614044\n",
      "\n",
      "idx: 462, landmark: x: 0.6035356521606445\n",
      "y: 0.4049713909626007\n",
      "z: -0.05306701734662056\n",
      "\n",
      "idx: 463, landmark: x: 0.6259541511535645\n",
      "y: 0.31264349818229675\n",
      "z: 0.019634798169136047\n",
      "\n",
      "idx: 464, landmark: x: 0.6175956726074219\n",
      "y: 0.31573355197906494\n",
      "z: 0.01094406470656395\n",
      "\n",
      "idx: 465, landmark: x: 0.6121129989624023\n",
      "y: 0.317658007144928\n",
      "z: 0.00017323945940006524\n",
      "\n",
      "idx: 466, landmark: x: 0.687373697757721\n",
      "y: 0.3073057234287262\n",
      "z: 0.025088248774409294\n",
      "\n",
      "idx: 467, landmark: x: 0.6977106332778931\n",
      "y: 0.30106478929519653\n",
      "z: 0.025864483788609505\n",
      "\n",
      "idx: 468, landmark: x: 0.5196311473846436\n",
      "y: 0.3173251152038574\n",
      "z: 0.026721738278865814\n",
      "\n",
      "idx: 469, landmark: x: 0.5315281748771667\n",
      "y: 0.31593433022499084\n",
      "z: 0.026721738278865814\n",
      "\n",
      "idx: 470, landmark: x: 0.5184952020645142\n",
      "y: 0.30720067024230957\n",
      "z: 0.026721738278865814\n",
      "\n",
      "idx: 471, landmark: x: 0.5075545310974121\n",
      "y: 0.31878167390823364\n",
      "z: 0.026721738278865814\n",
      "\n",
      "idx: 472, landmark: x: 0.5206109285354614\n",
      "y: 0.3274267017841339\n",
      "z: 0.026721738278865814\n",
      "\n",
      "idx: 473, landmark: x: 0.6595450043678284\n",
      "y: 0.3070313334465027\n",
      "z: 0.019900068640708923\n",
      "\n",
      "idx: 474, landmark: x: 0.6736773252487183\n",
      "y: 0.30704396963119507\n",
      "z: 0.019900068640708923\n",
      "\n",
      "idx: 475, landmark: x: 0.6599369645118713\n",
      "y: 0.2964932322502136\n",
      "z: 0.019900068640708923\n",
      "\n",
      "idx: 476, landmark: x: 0.6455585956573486\n",
      "y: 0.30692458152770996\n",
      "z: 0.019900068640708923\n",
      "\n",
      "idx: 477, landmark: x: 0.6593033075332642\n",
      "y: 0.31764209270477295\n",
      "z: 0.019900068640708923\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import matplotlib as plt\n",
    "import mediapipe as mp\n",
    "\n",
    "mp_face_mesh = mp.solutions.face_mesh\n",
    "mp_drawing = mp.solutions.drawing_utils\n",
    "mp_drawing_styles = mp.solutions.drawing_styles\n",
    "\n",
    "img_path = '../data/kkj/kkj04_lipsync3d/crop/00003.png'\n",
    "drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)\n",
    "\n",
    "with mp_face_mesh.FaceMesh(\n",
    "    static_image_mode=True,\n",
    "    max_num_faces=1,\n",
    "    refine_landmarks=True,\n",
    "    min_detection_confidence=0.5) as face_mesh:\n",
    "\n",
    "    image = cv2.imread(img_path)\n",
    "    results = face_mesh.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n",
    "    for idx, landmark in enumerate(results.multi_face_landmarks[0].landmark):\n",
    "          print('idx: {}, landmark: {}'.format(idx, landmark))\n",
    "\n",
    "    annotated_image = image.copy()\n",
    "    for face_landmarks in results.multi_face_landmarks:\n",
    "        mp_drawing.draw_landmarks(\n",
    "          image=annotated_image,\n",
    "          landmark_list=face_landmarks,\n",
    "          landmark_drawing_spec=drawing_spec,\n",
    "          connections=None,\n",
    "          connection_drawing_spec=None)\n",
    "        \n",
    "        nose = face_landmarks.landmark[2]\n",
    "        left_eye = face_landmarks.landmark[130]\n",
    "        right_eye = face_landmarks.landmark[359]\n",
    "\n",
    "        image_rows, image_cols, _ = image.shape\n",
    "        nose = mp_drawing._normalized_to_pixel_coordinates(nose.x, nose.y, image_cols, image_rows)\n",
    "        left_eye = mp_drawing._normalized_to_pixel_coordinates(left_eye.x, left_eye.y, image_cols, image_rows)\n",
    "        right_eye = mp_drawing._normalized_to_pixel_coordinates(right_eye.x, right_eye.y, image_cols, image_rows)\n",
    "\n",
    "        cv2.circle(annotated_image, nose, 2, mp_drawing.RED_COLOR, 2)\n",
    "        cv2.circle(annotated_image, left_eye, 2, mp_drawing.RED_COLOR, 2)\n",
    "        cv2.circle(annotated_image, right_eye, 2, mp_drawing.RED_COLOR, 2)\n",
    "\n",
    "    cv2.imwrite('annotated_image.png', annotated_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import librosa\n",
    "import librosa.display\n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "x = librosa.load('../data/kkj/kkj04_lipsync3d/audio/audio.wav',16000)[0]\n",
    "y = librosa.stft(x, n_fft=510, hop_length=160, win_length=480)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('/home/server01/jyeongho_workspace/3d_face_gcns/')\n",
    "import torch\n",
    "import os\n",
    "from lib.mesh_io import read_obj\n",
    "from gcn_util.utils import init_sampling\n",
    "import numpy as np\n",
    "refer_mesh = read_obj(os.path.join('../renderer', 'data', 'bfm09_face_template.obj'))\n",
    "laplacians, downsamp_trans, upsamp_trans, pool_size = init_sampling(\n",
    "refer_mesh, os.path.join('../renderer', 'data', 'params', 'bfm09_face'), 'bfm09_face')\n",
    "\n",
    "# laplacians = [(torch.FloatTensor(np.array(laplacian.todense())) - torch.diag(torch.ones(laplacian.shape[0]))).to_sparse() for laplacian in laplacians]\n",
    "downsamp_trans = [torch.FloatTensor(np.array(downsamp_tran.todense())) for downsamp_tran in downsamp_trans]\n",
    "upsamp_trans = [torch.FloatTensor(np.array(upsamp_tran.todense())) for upsamp_tran in upsamp_trans]\n",
    "\n",
    "downsamp_tran = torch.mm(torch.mm(downsamp_trans[2], downsamp_trans[1]), downsamp_trans[0])\n",
    "downsamp_tran_2232 = torch.mm(downsamp_trans[1], downsamp_trans[0])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "downsamp_tran = torch.zeros((68, 35709))\n",
    "landmark_index = torch.tensor([\n",
    "                27440, 27208, 27608, 27816, 35472, 34766, 34312, 34022, 33838, 33654,\n",
    "                33375, 32939, 32244, 16264, 16467, 16888, 16644, 31716, 31056, 30662,\n",
    "                30454, 30288, 29549, 29382, 29177, 28787, 28111,  8161,  8177,  8187,\n",
    "                8192,  9883,  9163,  8204,  7243,  6515, 14066, 12383, 11353, 10455,\n",
    "                11492, 12653,  5828,  4920,  3886,  2215,  3640,  4801, 10795, 10395,\n",
    "                8935,  8215,  7495,  6025,  5522,  6915,  7636,  8236,  8836,  9555,\n",
    "                10537,  9064,  8223,  7384,  5909,  7629,  8229,  8829\n",
    "            ])\n",
    "\n",
    "for i in range(68):\n",
    "    downsamp_tran[i, landmark_index[i]] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2966/2966 [00:00<00:00, 6973.10it/s]\n",
      "100%|██████████| 29060/29060 [00:04<00:00, 6996.77it/s]\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append('/home/server01/jyeongho_workspace/3d_face_gcns/')\n",
    "\n",
    "from audiodvp_utils import util\n",
    "\n",
    "delta_dir = \"../data/kkj/kkj_last/reenact_geometry\"\n",
    "delta_list = util.load_coef(delta_dir)\n",
    "delta_gt_list = util.load_coef(\"../data/kkj/kkj04/delta\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import dlib\n",
    "\n",
    "dlib.DLIB_USE_CUDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(256, 60001)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "import librosa\n",
    "\n",
    "\n",
    "audio_path = \"../data/kkj/kkj04_short/audio/audio.wav\"\n",
    "audio = librosa.load(audio_path,16000)[0]\n",
    "audio_stft = librosa.stft(audio, n_fft=510, hop_length=160, win_length=480)\n",
    "audio_stft.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import math\n",
    "import torch.nn.functional as F\n",
    "\n",
    "class MultiHeadAttn(nn.Module):\n",
    "    def __init__(self, dim_q, dim_k, dim_v, dim_out, num_heads=8):\n",
    "        super().__init__()\n",
    "        self.num_heads = num_heads\n",
    "        self.dim_out = dim_out\n",
    "        self.fc_q = nn.Linear(dim_q, dim_out, bias=False)\n",
    "        self.fc_k = nn.Linear(dim_k, dim_out, bias=False)\n",
    "        self.fc_v = nn.Linear(dim_v, dim_out, bias=False)\n",
    "        self.fc_out = nn.Linear(dim_out, dim_out)\n",
    "        self.ln1 = nn.LayerNorm(dim_out)\n",
    "        self.ln2 = nn.LayerNorm(dim_out)\n",
    "\n",
    "    def scatter(self, x):\n",
    "        return torch.cat(x.chunk(self.num_heads, -1), -3)\n",
    "\n",
    "    def gather(self, x):\n",
    "        return torch.cat(x.chunk(self.num_heads, -3), -1)\n",
    "\n",
    "    def attend(self, q, k, v, mask=None):\n",
    "        q_, k_, v_ = [self.scatter(x) for x in [q, k, v]]\n",
    "        A_logits = q_ @ k_.transpose(-2, -1) / math.sqrt(self.dim_out)\n",
    "        A = torch.softmax(A_logits, -1)\n",
    "        return self.gather(A @ v_)\n",
    "\n",
    "    def forward(self, q, k, v, mask=None):\n",
    "        q, k, v = self.fc_q(q), self.fc_k(k), self.fc_v(v)\n",
    "        out = self.ln1(q + self.attend(q, k, v, mask=mask))\n",
    "        out = self.ln2(out + F.relu(self.fc_out(out)))\n",
    "        return out\n",
    "\n",
    "\n",
    "class SelfAttn(MultiHeadAttn):\n",
    "    def __init__(self, dim_in, dim_out, num_heads=8):\n",
    "        super().__init__(dim_in, dim_in, dim_in, dim_out, num_heads)\n",
    "\n",
    "    def forward(self, x, mask=None):\n",
    "        return super().forward(x, x, x, mask=mask)\n",
    "\n",
    "model = SelfAttn(256, 256)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([32, 256, 1, 24])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = torch.randn((32, 256, 1, 24))\n",
    "a = A.permute((0, 3, 1, 2)).squeeze()\n",
    "a.unsqueeze(-1).permute(0, 2, 3, 1).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([2, 9600000])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "waveform.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(150,)\n",
      "(150, 1326)\n",
      "tensor([[-0.1296,  0.3318,  1.4108,  ...,  0.4191,  2.1836, -0.0064]])\n",
      "[-0.12962224  0.33178094  1.4107552  ...  0.4190533   2.183611\n",
      " -0.00639199]\n"
     ]
    }
   ],
   "source": [
    "print(pca.fit_transform(scaled_exp)[0].shape)\n",
    "print(pca.components_.shape)\n",
    "coord = torch.from_numpy(pca.fit_transform(scaled_exp)[0]).reshape(1, -1)\n",
    "comp = torch.from_numpy(pca.components_)\n",
    "print(torch.mm(coord, comp))\n",
    "print(scaled_exp[0])"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.8.3 64-bit ('jyeongho': conda)",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
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